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Inicio Revista Iberoamericana de Automática e Informática Industrial RIAI Análisis Comparativo de las técnicas utilizadas en un Sistema de Reconocimient...
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Vol. 14. Núm. 1.
Páginas 104-114 (enero - marzo 2017)
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Vol. 14. Núm. 1.
Páginas 104-114 (enero - marzo 2017)
Open Access
Análisis Comparativo de las técnicas utilizadas en un Sistema de Reconocimiento de Hojas de Planta
Comparative Analysis of the Techniques Used in a Recognition System of Plant Leaves
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Jair Cervantesa,
Autor para correspondencia
jcervantesc@uaemex.mx

Autor para correspondencia.
, Jesús Taltempaa, Farid García-Lamonta, José S. Ruiz Castillaa, Arturo Yee Rendonb, Laura D. Jalilia
a Posgrado e Investigación, Universidad Autónoma del Estado de México, Prolongación de Av. Zumpango s/n, Fracc. El Tejocote, Texcoco, 52346, México
b Facultad de Ciencias de la Computación, Universidad Autónoma de Sinaloa, Culiacán, Sinaloa, 80013, Mexico
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El desarrollo de sistemas de identificación de hojas de plantas es un reto actual que comprende numerosas aplicaciones que van desde alimentación, medicina, industria y medio ambiente. En la literatura actual, se han propuesto varias técnicas con el objetivo de identificar plantas en diversos campos de aplicación. Sin embargo, las técnicas actuales están restringidas al reconocimiento e identificación de tipos de plantas limitados, utilizando descriptores de características específicos. En este artículo, se realiza un análisis comparativo de diversos métodos de extracción de características (texturales, cromáticas y geométricas) y clasificaci¿on sobre conjuntos de plantas muy similares y disimiles entre sí. Doce conjuntos de hojas con características de forma similares son estudiados utilizando varios clasificadores. Se analiza el desempeño de diferentes combinaciones de características en cada conjunto. Los resultados obtenidos muestran que para incrementar el desempeño de los clasificadores estudiados, es necesaria una combinación de las diferentes técnicas de extracción de características, esta necesidad es mayor cuando se trabaja con conjuntos de hojas con características muy similares. Además, se muestra el mejor desempeño de un clasificador con otro.

Palabras clave:
Clasificación
Descriptores
SVM
Conjuntos de Datos
Características
Abstract

The development of vision systems for identifying plants by leaves is an important challenge which has numerous applications ranging from food, medicine, industry and environment. Recently, several techniques have been proposed in the literature in order to identify plants in various fields of application. However, current techniques are restricted to the recognition and identification of plants using specific descriptors. In this paper, is accomplished a comparative analysis using different methods of feature extraction (textural, chromatic and geometric) and different methods of classification. The experiments are executed on very similar plants. Twelve sets of leaves with similar shape characteristics are studied using several classifiers. The performance of different combinations of classifiers-descriptors are analyzed in detail for each set. The results show that a combination of different feature extraction techniques is necessary in order to improve the performance. This combination of descriptors is more necessary when the leaves have similar characteristics.

Keywords:
Classification
Descriptors
SVM
Data Sets
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